How socioeconomic and clinical factors impact prostate-cancer-specific and other-cause mortality in prostate cancer stratified by clinical stage: Competing-risk analysis.

BACKGROUND: The aim of this study was to analyze the causes of death and risk factors of prostate-cancer-specific mortality (PCSM) and other-cause mortality (OCM) at different clinical stages using data from the Surveillance, Epidemiology, and End Results database. METHODS: The characteristics and cause-specific death classifications of males with prostate cancer (PCa) were extracted. Multivariate competing-risk regression analysis was used to identify significant predictors and quantify the cumulative incidence of PCSM and OCM at different clinical stages. RESULTS: Of the 244,433 PCa patients who were included, 19,274 died from 7356 PCSM, and 11,918 from OCM. The proportion of PCSM gradually increased from 2010 to 2016. The risk factors for PCSM in the localized PCa stage included older age, not being married, living in a county with higher poverty rates, and higher PSA levels and Gleason scores. Meanwhile, Medicaid and lower education levels were the additional risk factors of OCM. The risk factors for PCSM in the regional PCa stage included older age, not being married, Medicaid, living in a county with higher poverty rates, and higher PSA levels and Gleason scores. Meanwhile, the income level did not affect OCM risk. The risk factors for PCSM in the distant metastatic PCa stage included a separated/divorced/widowed marital status, Medicaid, and higher PSA levels and Gleason scores. Meanwhile, older age, an unmarried or separated/divorced/widowed marital status, and higher PSA levels were risk factors for OCM. In addition, receiving both surgery and radiation was worse than just receiving surgery for PCa specific survival in localized and regional PCa patients. CONCLUSION: Some pretreatment and treatment factors may influence OCM that are not identical to those for PCSM at the corresponding stage. Decision-makers and managers should fully consider OCM to maximize treatment benefits for PCa.

Analysis of Prognostic Factors of Low-Grade Gliomas in Adults Using Time-Dependent Competing Risk Models: A Population Study Based on the Surveillance, Epidemiology, and End Results Database.

BACKGROUND: Because of multiple competing death outcomes and time-varying coefficients, using a Cox regression model to analyze the prognostic factors of low-grade gliomas (LGG) may lead to a possible bias. Therefore, we adopted time-dependent competing risk models to obtain accurate prognostic factors for LGG. METHODS: In this retrospective cohort study, data were extracted from patients enrolled in the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2018. Univariate analysis was performed using the cumulative incidence function (CIF) and Kaplan-Meier (KM) function. Time-dependent competing risk and Cox regression models were used in the multivariable analysis. RESULTS: A total of 2581 patients were diagnosed with low-grade glioma, among whom 889 died from low-grade glioma, 114 died from other causes, and the rest were alive. The time-dependent competing risk models indicated that age, sex, marital status, primary tumor site, histological type, tumor diameter, surgery, and year of diagnosis were significantly associated with low-grade glioma-specific death, and the relative effect of age, tumor diameter, surgery, oligodendroglioma, and mixed glioma on low-grade glioma-specific death changed over time. Compared with the competing risk models, the Cox regression model misestimated the hazard ratio (HR) of covariates on the outcome and even produced false-negative results. CONCLUSIONS: The time-dependent competing risk models were better than the Cox regression model for evaluating the impact of covariates on low-grade glioma-specific mortality in the presence of competing risks and time-varying coefficients. The models identified the prognostic factors of LGG more accurately than the Cox regression model.

The relationship between hematocrit and serum albumin levels difference and mortality in elderly sepsis patients in intensive care units-a retrospective study based on two large database.

BACKGROUND: Sepsis still threatens the lives of more than 300 million patients annually and elderly patients with sepsis usually have a more complicated condition and a worse prognosis. Existing studies have shown that both Hematocrit (HCT) and albumin (ALB) can be used as potential predictors of sepsis, and their difference HCT-ALB has a significant capacity to diagnose infectious diseases. Currently, there is no relevant research on the relationship between HCT-ALB and the prognosis of elderly sepsis patients. Therefore, this study aims to explore the association between HCT-ALB and mortality in elderly patients with sepsis. METHODS: This study was a multi-center retrospective study based on the Medical Information Mart for Intensive Care (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD) in elderly patients with sepsis. The optimal HCT-ALB cut-off point for ICU mortality was calculated by the Youden Index based on the eICU-CRD dataset, and multivariate logistic regressions were conducted to explore the association between HCT-ALB and ICU/hospital mortality in the two databases. Subgroup analyses were performed for different parameters and comorbidity status. RESULTS: The number of 16,127 and 3043 elderly sepsis patients were selected from two large intensive care databases (eICU-CRD and MIMIC-IV, respectively) in this study. Depending on the optimal cut-off point, patients in both eICU-CRD and MIMIC-IV were independently divided into low HCT-ALB (< 6.7) and high HCT-ALB (≥ 6.7) groups. The odds ratio (95%confidence interval) [OR (95CI%)] of the high HCT-ALB group were 1.50 (1.36,1.65) and 1.71 (1.58,1.87) for ICU and hospital mortality in the eICU-CRD database after multivariable adjustment. Similar trends in the ICU and hospital mortality [OR (95%CI) 1.41 (1.15,1.72) and 1.27 (1.07,1.51)] were observed in MIMIC-IV database. Subgroup analysis showed an interaction effect with SOFA score in the eICU-CRD database however not in MIMIC-IV dataset. CONCLUSIONS: High HCT-ALB (≥ 6.7) is associated with 1.41 and 1.27 times ICU and hospital mortality risk in elderly patients with sepsis. HCT-ALB is simple and easy to obtain and is a promising clinical predictor of early risk stratification for elderly sepsis patients in ICU.

Influence of ambulatory blood pressure-related indicators within 24 h on in-hospital death in sepsis patients.

Background: Sepsis is a serious public health problem worldwide. Blood pressure is one of the indicators that is closely monitored in intensive-care units, and it reflects complex interactions between the internal cardiovascular control mechanism and the external environment. We aimed to determine the impact of indicators related to the ambulatory blood pressure on the prognosis of sepsis patients. Methods: This retrospective study was based on the Medical Information Mart for Intensive Care IV database. Relevant information about sepsis patients was extracted according to specific inclusion and exclusion criteria. Examined parameters included the average blood pressure, blood pressure variability (BPV), and circadian rhythm, and the study outcome was in-hospital death. We investigated the effects of these indicators on the risk of in-hospital death among sepsis patients using Cox proportional-hazards models, restricted cubic splines analysis, and subgroup analysis. Results: This study enrolled 10,316 sepsis patients, among whom 2,117 died during hospitalization. All parameters except the nighttime variation coefficient of the diastolic blood pressure (DBP) were associated with in-hospital death of sepsis patients. All parameters except for fluctuations in DBP exhibited nonlinear correlations with the outcome. The subgroup analysis revealed that some of the examined parameters were associated with in-hospital death only in certain subgroups. Conclusion: Indicators related to the ambulatory blood pressure within 24 h are related to the prognosis of sepsis patients. When treating sepsis, in addition to blood pressure, attention should also be paid to BPV and the circadian rhythm in order to improve the prognosis and the survival rate.

Relationship between self-reported sleep duration during week-/work-days and metabolic syndrome from NHANES 2013 to 2016.

PURPOSE: This research aimed at determining the relationship between self-reported sleep duration during week-/work-days and metabolic syndrome (MetS) from NHANES 2013 to 2016. METHODS: This study analyzed data from 11,181 people aged 16 or older who took part in the NHANES (National Health and Nutrition Examination Surveys) from 2013 to 2016. A standard questionnaire was used to define self-reported sleep duration, and MetS was defined on the basis of the NCEP (National Cholesterol Education Program)/ATP III revised diagnostic criteria. Logistic regression and restricted cubic splines (RCS) models were used to assess the relationship between self-reported sleep duration and MetS. RESULTS: The overall prevalence of MetS in the study cohort was 26.1%, with 24.8% for males and 27.3% for females. After adjusting for potential confounding factors, MetS was significantly associated with self-reported short sleep duration (odds ratio = 1.16, 95% confidence interval = 1.03-1.31, P = 0.013) but not with long sleep duration (P = 0.117). RCS regression revealed that self-reported sleep duration was nonlinearly related to MetS (P for nonlinearity = 0.0026). The risk of MetS decreased with increased sleep duration for durations of less than 7 h/day, while there was no association for longer sleep durations. CONCLUSION: These results suggest that self-reported short sleep duration is a risk factor for MetS, while long sleep duration is not.

Sleep duration, genetic susceptibility, and Alzheimer's disease: a longitudinal UK Biobank-based study.

BACKGROUND: Alzheimer's disease (AD) is the most frequently occurring type of dementia. Concurrently, inadequate sleep has been recognized as a public health epidemic. Notably, genetic and environmental factors are now considered contributors to AD progression. OBJECTIVE: To assess the association between sleep duration, genetic susceptibility, and AD. METHODS AND RESULTS: Based on 483,507 participants from the UK Biobank (UKB) with an average follow-up of 11.3 years, there was a non-linear relationship between AD incidence and sleep duration (P for non-linear < 0.001) by restricted cubic splines (RCS). Sleep duration was categorized into short sleep duration (< 6 h/night), normal sleep duration (6-9 h/night), and long sleep duration (> 9 h/night). No statistically significant interaction was identified between sleep duration and the AD-GRS (Alzheimer's disease genetic risk score, P for interaction = 0.45) using Cox proportional risk model. Compared with the participants who had a low AD-GRS and normal sleep duration, there was associated with a higher risk of AD in participants with a low AD-GRS and long sleep duration (HR = 3.4806; 95% CI 2.0011-6.054, p < 0.001), participants with an intermediate AD-GRS and long sleep duration (HR = 2.0485; 95% CI 1.3491-3.1105, p < 0.001), participants with a high AD-GRS and normal sleep duration (HR = 1.9272; 95% CI 1.5361-2.4176, p < 0.001), and participants with a high AD-GRS and long sleep duration (HR = 5.4548; 95% CI 3.1367-9.4863, p < 0.001).In addition, there was no causal association between AD and sleep duration using Two Sample Mendelian randomization (MR). CONCLUSION: In the UKB population, though there was no causal association between AD and sleep duration analyzed using Two Sample MR, long sleep duration (> 9 h/night) was significantly associated with a higher risk of AD, regardless of high, intermediate or low AD-GRS. Prolonged sleep duration may be one of the clinical predictors of a higher risk of AD.

Antithrombotic Therapy Improves ICU Mortality of Septic Patients with Peripheral Vascular Disease.

Objective: The effectiveness of antithrombotic drugs for treating sepsis is controversial. Here, we explore the association between antithrombotic therapy and intensive care unit (ICU) mortality for septic patients with peripheral vascular disease. Methods: This retrospective cohort study uses data from the Medical Information Mart for Intensive Care (MIMIC)-III database. Kaplan-Meier survival analyses were used to examine mortality among different groups. Cox regression and marginal structural Cox models (MSCMs) were used to adjust for confounding factors. Main Results. The final cohort from the MIMIC-III database included 776 patients, of which 701 survived and 75 perished. The anticoagulant (AC) group and the antiplatelet-anticoagulation (AC-AP) group survived better than the group without antithrombotic treatment (non-AT). The AC and AC-AP groups showed a 0.363-fold and 0.373-fold risk of ICU mortality, respectively, compared with the non-AT group when controlling for age, gender, CRRT, alcohol, heart failure, hypertension, diabetes, obesity, renal failure, liver disease, INR, PT, PPT, and SpO2. Antiplatelet therapy did not reduce ICU mortality. The same trends were apparent from the MSCM. In addition, the AC-AP group exhibited a lower risk of bleeding complications. Conclusion: Although the antithrombotic group (AC and AC-AP groups) demonstrated a higher sequential organ failure assessment (SOFA) score than the group without antithrombotic treatment (non-AT group), the risk of ICU mortality was lower without increasing the risk of bleeding complications. Our study further suggested that anticoagulation therapy may benefit the prognosis of septic patients with peripheral vascular disease.

Risk factor analysis and nomogram for predicting in-hospital mortality in ICU patients with sepsis and lung infection.

BACKGROUND: Lung infection is a common cause of sepsis, and patients with sepsis and lung infection are more ill and have a higher mortality rate than sepsis patients without lung infection. We constructed a nomogram prediction model to accurately evaluate the prognosis of and provide treatment advice for patients with sepsis and lung infection. METHODS: Data were retrospectively extracted from the Medical Information Mart for Intensive Care (MIMIC-III) open-source clinical database. The definition of Sepsis 3.0 [10] was used, which includes patients with life-threatening organ dysfunction caused by an uncontrolled host response to infection, and SOFA score ≥ 2. The nomogram prediction model was constructed from the training set using logistic regression analysis, and was then internally validated and underwent sensitivity analysis. RESULTS: The risk factors of age, lactate, temperature, oxygenation index, BUN, lactate, Glasgow Coma Score (GCS), liver disease, cancer, organ transplantation, Troponin T(TnT), neutrophil-to-lymphocyte ratio (NLR), and CRRT, MV, and vasopressor use were included in the nomogram. We compared our nomogram with the Sequential Organ Failure Assessment (SOFA) score and Simplified Acute Physiology Score II (SAPSII), the nomogram had better discrimination ability, with areas under the receiver operating characteristic curve (AUROC) of 0.743 (95% C.I.: 0.713-0.773) and 0.746 (95% C.I.: 0.699-0.790) in the training and validation sets, respectively. The calibration plot indicated that the nomogram was adequate for predicting the in-hospital mortality risk in both sets. The decision-curve analysis (DCA) of the nomogram revealed that it provided net benefits for clinical use over using the SOFA score and SAPSII in both sets. CONCLUSION: Our new nomogram is a convenient tool for accurate predictions of in-hospital mortality among ICU patients with sepsis and lung infection. Treatment strategies that improve the factors considered relevant in the model could increase in-hospital survival for these ICU patients.

The association between continuous renal replacement therapy as treatment for sepsis-associated acute kidney injury and trend of lactate trajectory as risk factor of 28-day mortality in intensive care units.

BACKGROUND: Sepsis has high incidence and fatality rates in intensive care units, often leading to renal failure. The effectiveness of continuous renal replacement therapy (CRRT) in sepsis-associated acute kidney injury (S-AKI) patients is currently uncertain. AIM: Joint model was used to determine the association between CRRT and the lactate trajectory trend and how it correlated to 28-day mortality for S-AKI patient in ICU. METHODS: A retrospective study was applied to patients with sepsis and AKI, which were extracted from the MIMIC-III public database, with the endpoint being 28-day mortality. Every lactate level measurement within 28 days was observed and calculated using logarithms. Joint model combined the longitudinal analysis of the natural logarithm of the lactate level [log(lactate)] in longitudinal submodel and Cox regression by trajectory function, demonstrating the effects of CRRT on 28-day survival and log(lactate) changes, and its final relationship with the event status. RESULTS: Among the 717 S-AKI patients, 157 received CRRT. CRRT was not associated with 28-day mortality. After adjustments, the relationship between CRRT use and log(lactate) elevation was statistically significant. The parameter estimation of CRRT and log(lactate) indicated that using CRRT will increase log(lactate) by 0.041 in S-AKI patients. The joint model also instigated a fixed association between changes in the lactate level and the event result, revealing an exp value of (0.755) = 2.12, indicating that an increase of one unit in log(lactate) will increase the risk of 28-day mortality 2.12-times. CONCLUSION: There was no significant association between CRRT use and 28-day survival in S-AKI patients, and JM showed that CRRT use might be associated with elevation of longitudinal lactate levels. Therefore, additional attention should be paid to other treatments to control lactate levels when providing renal support for patients with S-AKI.

Influence of the trajectory of the urine output for 24 h on the occurrence of AKI in patients with sepsis in intensive care unit.

BACKGROUND: Sepsis-associated acute kidney injury (S-AKI) is a common and life-threatening complication in hospitalized and critically ill patients. This condition is an independent cause of death. This study was performed to investigate the correlation between the trajectory of urine output within 24 h and S-AKI. METHODS: Patients with sepsis were studied retrospectively based on the Medical Information Mart for Intensive Care IV. Latent growth mixture modeling was used to classify the trajectory of urine output changes within 24 h of sepsis diagnosis. The outcome of this study is AKI that occurs 24 h after sepsis. Cox proportional hazard model, Fine-Gray subdistribution proportional hazard model, and doubly robust estimation method were used to explore the risk of AKI in patients with different trajectory classes. RESULTS: A total of 9869 sepsis patients were included in this study, and their 24-h urine output trajectories were divided into five classes. The Cox proportional hazard model showed that compared with class 1, the HR (95% CI) values for classes 3, 4, and 5 were 1.460 (1.137-1.875), 1.532 (1.197-1.961), and 2.232 (1.795-2.774), respectively. Competing risk model and doubly robust estimation methods reached similar results. CONCLUSIONS: The trajectory of urine output within 24 h of sepsis patients has a certain impact on the occurrence of AKI. Therefore, in the early treatment of sepsis, close attention should be paid to changes in the patient's urine output to prevent the occurrence of S-AKI.

Obesity Paradox of All-Cause Mortality in 4,133 Patients Treated with Coronary Revascularization.

OBJECTIVES: The purpose of this study was to determine whether there is a dose-response relationship between body mass index (BMI) and all-cause mortality in patients after coronary revascularization. METHODS: The MIMIC-III database (version 1.4) was used as the sample population. For variables with less than 10% of values missing, we used the mice package of R software for multiple imputations. Cox regression was used to determine the risk factors of all-cause mortality in patients. RCSs were used to observe the relationship between BMI and all-cause mortality. Additional subgroup and sensitivity analyses were also performed to explore whether the conclusion can be applied to specific groups. RESULTS: Both univariate and multivariate Cox models indicated that the mortality risk was lower for overweight patients than for normal-weight patients (P < 0.05). In RCS models, BMI had a U-shaped relationship with all-cause mortality of patients after coronary artery bypass grafting (CABG) (P for nonlinearity = 0.0028). There was a weak U-shaped relationship between BMI and all-cause mortality after percutaneous coronary intervention (PCI), but the nonlinear relationship between these two parameters was not significant (P for nonlinearity = 0.1756). CONCLUSIONS: The obesity paradox does exist in patients treated with CABG and PCI. RCS analysis indicated that there was a U-shaped relationship between BMI and all-cause mortality in patients after CABG. After sex stratification, the relationship between BMI and all-cause mortality in male patients who received PCI was L-shaped, while the nonlinear relationship among females was not significant.

Examining More Lymph Nodes May Improve the Prognosis of Patients With Right Colon Cancer: Determining the Optimal Minimum Lymph Node Count.

OBJECTIVES: The objective is to determine the optimal minimum lymph node examination number for right colon cancer (RCC) patients. METHODS: We comprehensively analysed the Surveillance, Epidemiology and End Results database data from 2004 to 2016 to determine the 13-year trend in the number of lymph nodes examined among 108,703 left colon cancer and 165,937 RCC patients. 133,137 RCC patients eligible for inclusion were used to determine the optimal minimum for lymph node examination. We used restricted cubic splines to analyse the dose-response relationship between the number of lymph nodes examined and prognosis. X-tiles and decision trees were used to determine the optimal cutoff for the number of lymph nodes based on the survival outcomes of patients with RCC. The Kaplan-Meier method and COX model were used to estimate the overall survival and independent prognostic factors, and a prediction model was constructed. The C-index, calibration curve, net reclassification improvement and integrated discrimination improvement were used to determine the predictive performance of the model, and decision curve analysis was used to evaluate the benefits. RESULTS: Lymph node examinations were common among colon cancer patients over the 13-year study period. It is generally agreed that at least 12 lymph nodes must be examined to ensure proper dissection and accurate staging of RCC; however, the optimal number of lymph nodes to be examined is controversial. The dose-response relationship indicated that 12 was not the optimal minimum number of lymph nodes for RCC patients. X-tile and survival decision-tree analysis indicated that 20 nodes was the optimal number. Survival analysis indicated that <20 nodes examined was a risk factor for poor prognosis, and the classification performance was superior for 20 nodes compared to 12 nodes. CONCLUSION: Lymph node examination in RCC patients should be altered. Our research suggests that a 20-node measure may be more suitable for RCC patients.

Nomogram for predicting cancer-specific survival in undifferentiated pleomorphic sarcoma: A Surveillance, Epidemiology, and End Results -based study.

INTRODUCTION: The purpose of this study was to construct and validate a nomogram for predicting cancer-specific survival (CSS) in undifferentiated pleomorphic sarcoma (UPS) patients at 3, 5, and 8 years after the diagnosis. METHODS: Data for UPS patients were extracted from the SEER (Surveillance, Epidemiology, and End Results) database. The patients were randomly divided into a training cohort (70%) and a validation cohort (30%). The backward stepwise Cox regression model was used to select independent prognostic factors. All of the factors were integrated into the nomogram to predict the CSS rates in UPS patients at 3, 5, and 8 years after the diagnosis. The nomogram' s performance was then validated using multiple indicators, including the area under the time-dependent receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, decision-curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification improvement (NRI). RESULTS: This study included 2,009 UPS patients. Ten prognostic factors were identified after analysis of the Cox regression model in the training cohort, which were year of diagnosis, age, race, primary site, histological grade, T, N, M stage, surgery status, and insurance status. The nomogram was then constructed and validated internally and externally. The relatively high C-indexes and AUC values indicated that the nomogram has good discrimination ability. The calibration curves revealed that the nomogram was well calibrated. NRI and IDI values were both improved, indicating that our nomogram was superior to the AJCC (American Joint Committee on Cancer) system. DCA curves demonstrated that the nomogram was clinically useful. CONCLUSIONS: The first nomogram for predicting the prognosis of UPS patients has been constructed and validated. Its usability and performance showed that the nomogram can be applied to clinical practice. However, further external validation is still needed.

Incidence trends and survival prediction of urothelial cancer of the bladder: a population-based study.

BACKGROUND: The aim of this study is to determine the incidence trends of urothelial cancer of the bladder (UCB) and to develop a nomogram for predicting the cancer-specific survival (CSS) of postsurgery UCB at a population-based level based on the SEER database. METHODS: The age-adjusted incidence of UCB diagnosed from 1975 to 2016 was extracted, and its annual percentage change was calculated and joinpoint regression analysis was performed. A nomogram was constructed for predicting the CSS in individual cases based on independent predictors. The predictive performance of the nomogram was evaluated using the consistency index (C-index), net reclassification index (NRI), integrated discrimination improvement (IDI), a calibration plot and the receiver operating characteristics (ROC) curve. RESULTS: The incidence of UCB showed a trend of first increasing and then decreasing from 1975 to 2016. However, the overall incidence increased over that time period. The age at diagnosis, ethnic group, insurance status, marital status, differentiated grade, AJCC stage, regional lymph nodes removed status, chemotherapy status, and tumor size were independent prognostic factors for postsurgery UCB. The nomogram constructed based on these independent factors performed well, with a C-index of 0.823 and a close fit to the calibration curve. Its prediction ability for CSS of postsurgery UCB is better than that of the existing AJCC system, with NRI and IDI values greater than 0 and ROC curves exhibiting good performance for 3, 5, and 8 years of follow-up. CONCLUSIONS: The nomogram constructed in this study might be suitable for clinical use in improving the clinical predictive accuracy of the long-term survival for postsurgery UCB.

Relationship Between Body Mass Index and Kidney Stones Based on Dose-Response Analyses Using Restricted Cubic Splines Applied to NHANES 2011-2016 Data.

OBJECTIVE: The objective of the study was to estimate the dose-response relationship between body mass index (BMI) and the self-reported prevalence of kidney stones based on a restricted cubic spline (RCS) method. METHODS: This cross-sectional study analyzed 13,223 adults aged ≥20 years who had participated in the National Health and Nutrition Examination Survey performed during 2011-2016. Kidney stones were identified using a standard questionnaire, and physical examinations were used to determine BMI. Logistic regression was used to assess the relationship between BMI and the prevalence of kidney stones, with the dose-response relationship explored using RCSs. RESULTS: The overall prevalence of kidney stones was 9.7%: 10.6% in males and 8.9% in females. After adjusting for potential confounders, compared with those with a BMI in quartile 1, the odds ratios of kidney stones among those with BMIs in quartiles 2, 3, and 4 were 1.45, 1.60, and 2.00, respectively (95% confidence interval = 1.21-1.75, 1.33-1.92, and 1.67-2.39; all P < .001). Multivariate RCS regression revealed that BMI was related to kidney stones in a nonlinear manner (P for nonlinearity <0.001). There was a significant positive relationship, with the curves being steeper when BMI was <28 kg/m2. CONCLUSION: This analysis of National Health and Nutrition Examination Survey data has demonstrated that BMI is significantly associated with the prevalence of kidney stones.

A prognostic nomogram for the cancer-specific survival of patients with upper-tract urothelial carcinoma based on the Surveillance, Epidemiology, and End Results Database.

BACKGROUND: The aim of this study was to establish a comprehensive nomogram for the cancer-specific survival (CSS) of patients with upper-tract urothelial carcinoma (UTUC) and compare it with the traditional American Joint Committee on Cancer (AJCC) staging system in order to determine its reliability. METHODS: This study analyzed 9505 patients with UTUC in the Surveillance, Epidemiology, and End Results (SEER) database. R software was used to randomly divided the patients in a 7-to-3 ratio to form a training cohort (n = 6653) and a validation cohort (n = 2852). Multivariable Cox regression was used to identify predictive variables. The new survival model was compared with the AJCC prognosis model using the concordance index (C-index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA). RESULTS: We have established a nomogram for determining the 3-, 5-, and 8-year CSS probabilities of UTUC patients. The nomogram indicates that the AJCC stage has the greatest influence on CSS in UTUC, followed by the age at diagnosis, surgery status, tumor size, radiotherapy status, histological grade, marital status, chemotherapy status, race, and finally sex. The C-index was higher for the nomogram than the AJCC staging system in both the training cohort (0.785 versus 0.747) and the validation cohort (0.779 versus 0.739). Calibration plotting demonstrated that the model has good calibration ability. The AUC, NRI, IDI, and DCA of the nomogram showed that it performs better than the AJCC staging system alone. CONCLUSIONS: This study is the first to establish a comprehensive UTUC nomogram based on the SEER database and evaluate it using a series of indicators. Our novel nomogram can help clinical staff to predict the 3-, 5-, and 8-year CSS probabilities of UTUC patients more accurately than using the AJCC staging system.

Establishment and Validation of a Nomogram for Tonsil Squamous Cell Carcinoma: A Retrospective Study Based on the SEER Database.

This study aimed to establish and validate a comprehensive nomogram for predicting the cause-specific survival (CSS) probability in tonsillar squamous cell carcinoma (TSCC). We screened and extracted data from the SEER (Surveillance, Epidemiology, and End Results) database for the period 2004 to 2016. We randomly divided the 7243 identified patients into a training cohort (70%) for constructing the model and a validation cohort (30%) for evaluating the model using R software. Multivariate Cox stepwise regression was used to select predictive variables. The concordance index (C-index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the model. The multivariate Cox stepwise regression analysis successfully established a nomogram for the 1-, 3-, and 5-year CSS probabilities for TSCC patients. The C-index, AUC, NRI, and IDI were all showed that the model has good discrimination. The calibration plots were very close to the standard lines, indicating that the model has a good degree of calibration, and the DCA curve further illustrated that the model has good clinical validity. We have established the first nomogram for predicting the 1-, 3-, and 5-year CSS probabilities for TSCC based on a large retrospective sample. Our rigorous validation and evaluation indicated that the model can provide useful guidance to clinical workers making clinical decisions about individual patients.

Competing-Risks Model for Predicting the Postoperative Prognosis of Patients with Papillary Thyroid Adenocarcinoma Based on The Surveillance, Epidemiology, and End Results (SEER) Database.

BACKGROUND The aim of this study was to identify accurate prognostic factors for postoperative papillary thyroid adenocarcinoma (PTAC) using a competing-risks model based on data from the Surveillance, Epidemiology, and End Results (SEER) database. MATERIAL AND METHODS Data on patients with PTAC who had received surgery between 2010 and 2015 in the SEER database were extracted. A univariate analysis was performed while considering competing risks using the cumulative incidence function, with Nelson-Aalen cumulative risk curves of the incidence function for PTAC-specific death were calculated and then compared between 2 groups using Gray's test. To identify the factors that affect the cumulative incidence of PTAC-specific death, a multivariate analysis using the Fine-Gray model was performed. RESULTS The 8324 eligible surgical PTAC patients included 101 patients who died from PTAC and 129 patients who died from other causes. The univariate Gray's test revealed that the cumulative incidence rate for events of interest was significantly affected (P<0.05) by age, sex, marital status, metastasis, differentiation grade, American Joint Committee on Cancer (AJCC) stage, radiation status, chemotherapy status, regional lymph nodes removal, and tumor size. Multivariate competing-risks analyses showed that age, sex, metastasis, differentiation grade, radiation status, chemotherapy status, and tumor size were independent risk factors for the postoperative prognosis of PTAC patients (P<0.05). The results of multivariate Cox regression were different, with marital status also appearing as an independent risk factor. CONCLUSIONS This study established a competing-risks analysis model to evaluate the risk factors of surgical PTAC patients. Our findings may be useful for improving patient prognoses and decision-making when providing individualized treatments.

Global, regional, and national burdens of bladder cancer in 2017: estimates from the 2017 global burden of disease study.

BACKGROUND: The aim of this study is to describe the prevalence and mortality of bladder cancer (BCa) using data obtained in the Global Burden of Disease study performed in 2017 (GBD 2017). METHODS: Data on BCa for 2017, including prevalence, mortality, and disability-adjusted life years (DALYs), were obtained from GBD 2017 at the global, regional, and national levels. We also analyzed the association of BCa burden with the country development level. RESULTS: There were 2.63 million BCa cases estimated from the GBD 2017 data, with 200,000 persons dying of BCa, resulting in 3.60 million DALYs in 2017. The age-standardized prevalence (ASP) of BCa was 32.91/100,000 persons, and age-standardized death rate (ASDR) was 2.57/100,000 persons. The ASP and ASDR of BCa were higher in males than in females, and higher in people older than 60 years. The ASP and ASDR of BCa were higher in Western Europe and Central Europe than in South Asia, Andean Latin America, and Central Latin America, and higher in countries with a higher sociodemographic index (SDI). Correlation analysis identified that the ASP and ASDR of BCa were positively correlated with the country SDI (P < 0.0001 and ρ = 0.68 for ASP, and P = 0.0048 and ρ = 0.20 for ASDR). In addition, 33.72% deaths and 36.80% DALYs caused by BCa could be attributed to smoking globally. CONCLUSION: The prevalence and mortality of BCa were very high in 2017, especially in high-SDI countries. Smoking-cessation strategies should be strengthened to control the burden associated with BCa.

Association between physical activity and kidney stones based on dose-response analyses using restricted cubic splines.

BACKGROUND: This study aimed to determine whether there is a dose-response relationship between physical activity and the self-reported prevalence of kidney stone, based on a restricted cubic splines (RCS) method. METHODS: This study analyzed 8931 adults aged ≥20 years who had participated in the National Health and Nutrition Examination Survey (NHANES) during 2013-16. Kidney stones and physical activity were defined using a standard questionnaire, and metabolic equivalents (MET) were used to quantify the physical activity level. Logistic regression was used to assess the association between physical activity and the risk of kidney stones, and the dose-response relationship was explored using RCS. RESULTS: Kidney stones were present in 10.3% of the analyzed individuals: 11.5% of males and 9.2% of females. After adjusting for potential confounders, compared with the first quartile (Q1) of MET, the odds ratios (ORs) of kidney stones for those with Q2, Q3 and Q4 of MET were 0.72 [95% confidence interval (CI)=0.59-0.87], 0.77 (95% CI = 0.63-0.93) and 0.63 (95% CI = 0.51-0.78), respectively (all P < 0.01). The RCS regression showed that physical activity was related to kidney stones in a non-linear manner (P for non-linearity = 0.0100). The prevalence of kidney stones decreasing as physical activity increased, reaching a plateau for physical activity at approximately 2480 MET-min week-1 (OR = 0.75, 95% CI = 0.63-0.91). CONCLUSIONS: Physical activity is inversely associated with the prevalence of kidney stones, and the dose-response relationship has a plateau, after which the prevalence of kidney stones does not change with the increase of physical activity.